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» Robust model selection using fast and robust bootstrap
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ESANN
2003
13 years 6 months ago
Fast approximation of the bootstrap for model selection
The bootstrap resampling method may be efficiently used to estimate the generalization error of a family of nonlinear regression models, as artificial neural networks. The main dif...
Geoffroy Simon, Amaury Lendasse, Vincent Wertz, Mi...
ICCV
2009
IEEE
13 years 3 months ago
Robust facial feature tracking using selected multi-resolution linear predictors
This paper proposes a learnt data-driven approach for accurate, real-time tracking of facial features using only intensity information. Constraints such as a-priori shape models o...
Eng-Jon Ong, Yuxuan Lan, Barry Theobald, Richard H...
CSDA
2007
152views more  CSDA 2007»
13 years 5 months ago
Robust variable selection using least angle regression and elemental set sampling
In this paper we address the problem of selecting variables or features in a regression model in the presence of both additive (vertical) and leverage outliers. Since variable sel...
Lauren McCann, Roy E. Welsch
ICCV
2003
IEEE
14 years 7 months ago
Nonmetric Lens Distortion Calibration: Closed-form Solutions, Robust Estimation and Model Selection
This paper addresses the problem of calibrating camera lens distortion, which can be signi?cant in medium to wide angle lenses. While almost all existing nonmetric distortion cali...
Moumen T. El-Melegy, Aly A. Farag
ICIP
2006
IEEE
14 years 7 months ago
Robust Object Detection using Fast Feature Selection from Huge Feature Sets
This paper describes an efficient feature selection method that quickly selects a small subset out of a given huge feature set; for building robust object detection systems. In th...
Duy-Dinh Le, Shin'ichi Satoh